Digitaw image processing

This articwe is about madematicaw processing of digitaw images. For artistic processing of images, see Image editing. For compression awgoridms, see Image compression.

In computer science, digitaw image processing is de use of a digitaw computer to processdigitaw images drough an awgoridm.[1][2] As a subcategory or fiewd of digitaw signaw processing, digitaw image processing has many advantages over anawog image processing. It awwows a much wider range of awgoridms to be appwied to de input data and can avoid probwems such as de buiwd-up of noise and distortion during processing. Since images are defined over two dimensions (perhaps more) digitaw image processing may be modewed in de form of muwtidimensionaw systems. The generation and devewopment of digitaw image processing are mainwy affected by dree factors: first, de devewopment of computers; second, de devewopment of madematics (especiawwy de creation and improvement of discrete madematics deory); dird, de demand for a wide range of appwications in environment, agricuwture, miwitary, industry and medicaw science has increased.

Many of de techniqwes of digitaw image processing, or digitaw picture processing as it often was cawwed, were devewoped in de 1960s, at Beww Laboratories, de Jet Propuwsion Laboratory, Massachusetts Institute of Technowogy, University of Marywand, and a few oder research faciwities, wif appwication to satewwite imagery, wire-photo standards conversion, medicaw imaging, videophone, character recognition, and photograph enhancement.[3] The purpose of earwy image processing was to improve de qwawity of de image. It was aimed for human beings to improve de visuaw effect of peopwe. In image processing, de input is a wow-qwawity image, and de output is an image wif improved qwawity. Common image processing incwude image enhancement, restoration, encoding, and compression, uh-hah-hah-hah. The first successfuw appwication was de American Jet Propuwsion Laboratory (JPL). They used image processing techniqwes such as geometric correction, gradation transformation, noise removaw, etc. on de dousands of wunar photos sent back by de Space Detector Ranger 7 in 1964, taking into account de position of de sun and de environment of de moon, uh-hah-hah-hah. The impact of de successfuw mapping of de moon's surface map by de computer has been a huge success. Later, more compwex image processing was performed on de nearwy 100,000 photos sent back by de spacecraft, so dat de topographic map, cowor map and panoramic mosaic of de moon were obtained, which achieved extraordinary resuwts and waid a sowid foundation for human wanding on de moon, uh-hah-hah-hah.[4]

The cost of processing was fairwy high, however, wif de computing eqwipment of dat era. That changed in de 1970s, when digitaw image processing prowiferated as cheaper computers and dedicated hardware became avaiwabwe. This wed to images being processed in reaw-time, for some dedicated probwems such as tewevision standards conversion. As generaw-purpose computers became faster, dey started to take over de rowe of dedicated hardware for aww but de most speciawized and computer-intensive operations. Wif de fast computers and signaw processors avaiwabwe in de 2000s, digitaw image processing has become de most common form of image processing, and is generawwy used because it is not onwy de most versatiwe medod, but awso de cheapest.

The charge-coupwed device was invented by Wiwward S. Boywe and George E. Smif at Beww Labs in 1969.[7] Whiwe researching MOS technowogy, dey reawized dat an ewectric charge was de anawogy of de magnetic bubbwe and dat it couwd be stored on a tiny MOS capacitor. As it was fairwy straighforward to fabricate a series of MOS capacitors in a row, dey connected a suitabwe vowtage to dem so dat de charge couwd be stepped awong from one to de next.[5] The CCD is a semiconductor circuit dat was water used in de first digitaw video cameras for tewevision broadcasting.[8]

In 1972, de engineer from British company EMI Housfiewd invented de X-ray computed tomography device for head diagnosis, which is what we usuawwy cawwed CT(Computer Tomography). The CT nucweus medod is based on de projection of de human head section and is processed by computer to reconstruct de cross-sectionaw image, which is cawwed image reconstruction, uh-hah-hah-hah. In 1975, EMI successfuwwy devewoped a CT device for de whowe body, which obtained a cwear tomographic image of various parts of de human body. In 1979, dis diagnostic techniqwe won de Nobew Prize.[4] Digitaw image processing technowogy for medicaw appwications was inducted into de Space Foundation Space Technowogy Haww of Fame in 1994.[24]

Digitaw image processing awwows de use of much more compwex awgoridms, and hence, can offer bof more sophisticated performance at simpwe tasks, and de impwementation of medods which wouwd be impossibwe by anawogue means.

In particuwar, digitaw image processing is a concrete appwication of, and a practicaw technowogy based on:

To appwy de affine matrix to an image, de image is converted to matrix in which each entry corresponds to de pixew intensity at dat wocation, uh-hah-hah-hah. Then each pixew's wocation can be represented as a vector indicating de coordinates of dat pixew in de image, [x, y], where x and y are de row and cowumn of a pixew in de image matrix. This awwows de coordinate to be muwtipwied by an affine-transformation matrix, which gives de position dat de pixew vawue wiww be copied to in de output image.

However, to awwow transformations dat reqwire transwation transformations, 3 dimensionaw homogeneous coordinates are needed. The dird dimension is usuawwy set to a non-zero constant, usuawwy 1, so dat de new coordinate is [x, y, 1]. This awwows de coordinate vector to be muwtipwied by a 3 by 3 matrix, enabwing transwation shifts. So de dird dimension, which is de constant 1, awwows transwation, uh-hah-hah-hah.

Because matrix muwtipwication is associative, muwtipwe affine transformations can be combined into a singwe affine transformation by muwtipwying de matrix of each individuaw transformation in de order dat de transformations are done. This resuwts in a singwe matrix dat, when appwied to a point vector, gives de same resuwt as aww de individuaw transformations performed on de vector [x, y, 1] in seqwence. Thus a seqwence of affine transformation matrices can be reduced to a singwe affine transformation matrix.

For exampwe, 2 dimensionaw coordinates onwy awwow rotation about de origin (0, 0). But 3 dimensionaw homogeneous coordinates can be used to first transwate any point to (0, 0), den perform de rotation, and wastwy transwate de origin (0, 0) back to de originaw point (de opposite of de first transwation). These 3 affine transformations can be combined into a singwe matrix, dus awwowing rotation around any point in de image.[27]